SecurityGauge® Now Providing Retailers with Updated Crime Analytics, Maps & Data for 2016

Location, Inc. has updated its predictive analytics, scores and heat maps for violent and property crimes in its SecurityGauge® platform for 2016.

SecurityGauge’s annual crime update is unique in that it collects raw data reported from over 18,000 local law enforcement agencies across the U.S., and uses a relational database to assign reported crimes from every agency (e.g., municipal police, campus police, port authority, transit, etc.) to the localities for which they have law enforcement responsibility.

With this exclusive database, SecurityGauge® then uses its Ph.D.-developed computer models to statistically predict the rates for every major type of crime (violent and property) with 33-foot resolution across the United States.

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Historically, due to lack of significant, direct statistical correlation to shrink, violent crime rates and retail fraud, loss prevention teams have often overlooked crime risk analytics in critical security decisions. SecurityGauge crime analytics have shown a predictive accuracy greater than 92% for burglary, fraud, robbery and disturbance rates in various retail segments, including sporting goods, discount and drug stores, allowing retailers to confidently incorporate crime risk in the security decision making process.

“Our retail customers have not only used SecurityGauge® crime analytics to reduce shrink, but also to improve employee safety, security staffing and site selection,” said Andrew Couture, VP of sales and marketing, Location, Inc. “For example, one of our customers was opening a new store with a better lease and higher foot traffic down the street from its current location. Due to SecurityGauge’s 33-foot resolution, our customer was able to identify a high-risk area within close proximity to the new location, allowing them to justify why additional security resources should be factored into their budget.”

For more information or to run a free report, visit www.SecurityGauge.com.

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